Heng Lian - RankMe

126 papers A* 1B 1Journal 123Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FinVault: Benchmarking Financial Agent Safety in Execution-Grounded Environments. CoRR Zhi Yang, Runguo Li, Qiqi Qiang, Jiashun Wang, Fangqi Lou, Mengping Li, Dongpo Cheng, Rui Xu, Heng Lian, Shuo Zhang, Xiaolong Liang, Xiaoming Huang, Zheng Wei, Zhaowei Liu, Xin Guo, Huacan Wang, Ronghao Chen, Liwen Zhang
2026	J	`jnl`	Linear convergence of proximal gradient method for linear sparse SVM. Neural Networks Xiaoqi Jiao, Heng Lian, Jiamin Liu, Yingying Zhang
2026	J	`jnl`	MemGovern: Enhancing Code Agents through Learning from Governed Human Experiences. CoRR Qihao Wang, Ziming Cheng, Shuo Zhang, Fan Liu, Rui Xu, Heng Lian, Kunyi Wang, Xiaoming Yu, Jianghao Yin, Sen Hu, Yue Hu, Shaolei Zhang, Yanbing Liu, Ronghao Chen, Huacan Wang
2026	J	`jnl`	Randomized tensor decomposition and optimization in the tucker and tensor train formats. J. Comput. Appl. Math. Wenqi Lu, Hongmei Lin, Heng Lian
2026	J	`jnl`	SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents. CoRR Yuhang Wang, Yuling Shi, Mo Yang, Rongrui Zhang, Shilin He, Heng Lian, Yuting Chen, Siyu Ye, Kai Cai, Xiaodong Gu
2026	J	`jnl`	Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning. CoRR Chengwen Liu, Xiaomin Yu, Zhuoyue Chang, Zhe Huang, Shuo Zhang, Heng Lian, Kunyi Wang, Rui Xu, Sen Hu, Jianheng Hou, Hao Peng, Chengwei Qin, Xiaobin Hu, Hong Peng, Ronghao Chen, Huacan Wang
2025	—	`conf`	AI-Driven Literature Mining for Intelligent Synthesis Design. ICDM (Workshops) Heng Lian, Lei Du, Jian Wu, Yi He
2025	J	`jnl`	Communication-efficient transfer learning for adaptive Huber regression. Stat. Comput. Jichen Yang, Lei Wang, Heng Lian
2025	J	`jnl`	Debiased transfer learning estimation and inference for multinomial regression. Stat. Comput. Jichen Yang, Lei Wang, Heng Lian
2025	J	`jnl`	Decentralized Learning of Quantile Regression: A Smoothing Approach. J. Comput. Graph. Stat. Jianwei Shi, Yue Wang, Zhongyi Zhu, Heng Lian
2025	J	`jnl`	Decentralized Nonconvex Low-rank Matrix Recovery. IEEE Trans. Image Process. Junzhuo Gao, Heng Lian
2025	J	`jnl`	Distributed Semi-Supervised Inference for Generalized Linear Models With Block-Wise Missing Covariates. IEEE Trans. Inf. Theory Ziyuan Wang, Jin Liu, Jun Shao, Heng Lian, Lei Wang
2025	J	`jnl`	Distributed iterative hard thresholding for variable selection in Tobit models. Comput. Stat. Data Anal. Changxin Yang, Zhongyi Zhu, Hongmei Lin, Zengyan Fan, Heng Lian
2025	J	`jnl`	Heterogeneity-aware debiased machine learning for high-dimensional partially linear models. Stat. Comput. Yining Wu, Lei Wang, Heng Lian
2025	J	`jnl`	Improved analysis of supervised learning in the RKHS with random features: Beyond least squares. Neural Networks Jiamin Liu, Lei Wang, Heng Lian
2025	J	`jnl`	Kernel-Based Decentralized Policy Evaluation for Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. Jiamin Liu, Heng Lian
2025	J	`jnl`	Kernel-Based Regularized Learning with Random Projections: Beyond Least Squares. SIAM J. Math. Data Sci. Jiamin Liu, Junzhuo Gao, Heng Lian
2025	J	`jnl`	Optimal Decorrelated Score Subsampling for High-Dimensional Generalized Linear Models Under Measurement Constraints. J. Comput. Graph. Stat. Yujing Shao, Lei Wang, Heng Lian
2025	J	`jnl`	Optimal decorrelated score subsampling for Cox regression with massive survival data. Neurocomputing Yujing Shao, Zhaohan Hou, Lei Wang, Heng Lian
2025	J	`jnl`	Optimal distributed subsampling for expected shortfall regression via Neyman-orthogonal score. Knowl. Based Syst. Xing Li, Lei Wang, Heng Lian
2025	J	`jnl`	Optimal distributed subsampling under heterogeneity. Stat. Comput. Yujing Shao, Lei Wang, Heng Lian
2025	J	`jnl`	Optimal subsampling for high-dimensional partially linear models via machine learning methods. J. Mach. Learn. Res. Yujing Shao, Lei Wang, Heng Lian, HaiYing Wang
2025	J	`jnl`	SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution. CoRR Han Li, Yuling Shi, Shaoxin Lin, Xiaodong Gu, Heng Lian, Xin Wang, Yantao Jia, Tao Huang, Qianxiang Wang
2025	J	`jnl`	SWE-Exp: Experience-Driven Software Issue Resolution. CoRR Silin Chen, Shaoxin Lin, Xiaodong Gu, Yuling Shi, Heng Lian, Longfei Yun, Dong Chen, Weiguo Sun, Lin Cao, Qianxiang Wang
2025	J	`jnl`	Sample Efficient Nonparametric Regression via Low-Rank Regularization. J. Comput. Graph. Stat. Jiakun Jiang, Jiahao Peng, Heng Lian
2025	J	`jnl`	Sample efficient reinforcement learning via low-rank regularization. Knowl. Based Syst. Jiamin Liu, Heng Lian
2025	J	`jnl`	Sparse and debiased Lasso estimation and statistical inference for long time series via divide-and-conquer. Stat. Comput. Jin Liu, Wei Ma, Lei Wang, Heng Lian
2025	J	`jnl`	Sparse estimation and inference for prediction-powered semi-supervised linear regression. Stat. Comput. Zihao Song, Jicai Liu, Lei Wang, Heng Lian, Weihua Zhao
2024	J	`jnl`	Adaptive Huber trace regression with low-rank matrix parameter via nonconvex regularization. J. Complex. Xiangyong Tan, Ling Peng, Heng Lian, Xiaohui Liu
2024	J	`jnl`	Distributed Estimation of Support Vector Machines for Matrix Data. IEEE Trans. Neural Networks Learn. Syst. Wangli Xu, Jiamin Liu, Heng Lian
2024	J	`jnl`	Distributed statistical estimation in quantile regression over a network. Signal Process. Yue Wang, Wenqi Lu, Heng Lian
2024	J	`jnl`	Image classification based on tensor network DenseNet model. Appl. Intell. Chunyang Zhu, Lei Wang, Weihua Zhao, Heng Lian
2024	J	`jnl`	Linear convergence of decentralized estimation for statistical estimation using gradient method. Neurocomputing Wangli Xu, Kehan Wang, Heng Lian
2024	J	`jnl`	More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization. J. Mach. Learn. Res. Xu Liu, Heng Lian, Jian Huang
2024	J	`jnl`	Robust low tubal rank tensor recovery via L2E criterion. Pattern Recognit. Zihao Song, Xiangjian Xu, Heng Lian, Weihua Zhao
2024	J	`jnl`	Statistical performance of quantile tensor regression with convex regularization. J. Multivar. Anal. Wenqi Lu, Zhongyi Zhu, Rui Li, Heng Lian
2023	J	`jnl`	Best subset selection for high-dimensional non-smooth models using iterative hard thresholding. Inf. Sci. Yue Wang, Wenqi Lu, Heng Lian
2023	J	`jnl`	Communication-efficient estimation of quantile matrix regression for massive datasets. Comput. Stat. Data Anal. Yaohong Yang, Lei Wang, Jiamin Liu, Rui Li, Heng Lian
2023	J	`jnl`	Functional additive expectile regression in the reproducing kernel Hilbert space. J. Multivar. Anal. Yuzi Liu, Ling Peng, Qing Liu, Heng Lian, Xiaohui Liu
2023	J	`jnl`	Image recognition and classification with HOG based on nonlinear support tensor machine. Multim. Tools Appl. Chunyang Zhu, Weihua Zhao, Heng Lian
2023	J	`jnl`	On Linear Convergence of ADMM for Decentralized Quantile Regression. IEEE Trans. Signal Process. Yue Wang, Heng Lian
2023	J	`jnl`	On Optimal Learning With Random Features. IEEE Trans. Neural Networks Learn. Syst. Jiamin Liu, Heng Lian
2023	J	`jnl`	Properties of Standard and Sketched Kernel Fisher Discriminant. IEEE Trans. Pattern Anal. Mach. Intell. Jiamin Liu, Wangli Xu, Fode Zhang, Heng Lian
2023	J	`jnl`	Semiparametric function-on-function quantile regression model with dynamic single-index interactions. Comput. Stat. Data Anal. Hanbing Zhu, Yuanyuan Zhang, Yehua Li, Heng Lian
2023	J	`jnl`	Semiparametric penalized quadratic inference functions for longitudinal data in ultra-high dimensions. J. Multivar. Anal. Brittany Green, Heng Lian, Yan Yu, Tianhai Zu
2023	J	`jnl`	Value iteration for streaming data on a continuous space with gradient method in an RKHS. Neural Networks Jiamin Liu, Wangli Xu, Yue Wang, Heng Lian
2022	J	`jnl`	Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions. J. Mach. Learn. Res. Shaogao Lv, Heng Lian
2022	A*	`conf`	Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space. NeurIPS Heng Lian
2022	J	`jnl`	Life History Recorded in the Vagino-cervical Microbiome Along with Multi-omes. Genom. Proteom. Bioinform. Zhuye Jie, Chen Chen, Lilan Hao, Fei Li, Liju Song, Xiaowei Zhang, Jie Zhu, Liu Tian, Xin Tong, Kaiye Cai, Zhe Zhang, Yanmei Ju, Xinlei Yu, Ying Li, Hongcheng Zhou, Haorong Lu, Xuemei Qiu, Qiang Li, Yunli Liao, Dongsheng Zhou, Heng Lian, Yong Zuo, Xiaomin Chen, Weiqiao Rao, Yan Ren, Yuan Wang, Jin Zi, Rong Wang, Na Liu, Jinghua Wu, Wei Zhang, Xiao Liu, Yang Zong, Weibin Liu, Liang Xiao, Yong Hou, Xun Xu, Huanming Yang, Jian Wang, Karsten Kristiansen, Huijue Jia
2022	J	`jnl`	Sparse high-dimensional semi-nonparametric quantile regression in a reproducing kernel Hilbert space. Comput. Stat. Data Anal. Yue Wang, Yan Zhou, Rui Li, Heng Lian
2022	J	`jnl`	Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification. J. Mach. Learn. Res. Yingying Zhang, Yan-Yong Zhao, Heng Lian
2021	J	`jnl`	Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection. Inf. Sci. Fode Zhang, Rui Li, Heng Lian
2021	J	`jnl`	Distributed Partially Linear Additive Models With a High Dimensional Linear Part. IEEE Trans. Signal Inf. Process. over Networks Yue Wang, Weiping Zhang, Heng Lian
2021	J	`jnl`	Distributed learning for sketched kernel regression. Neural Networks Heng Lian, Jiamin Liu, Zengyan Fan
2021	J	`jnl`	Learning Rate for Convex Support Tensor Machines. IEEE Trans. Neural Networks Learn. Syst. Heng Lian
2021	J	`jnl`	Optimal prediction for high-dimensional functional quantile regression in reproducing kernel Hilbert spaces. J. Complex. Guangren Yang, Xiaohui Liu, Heng Lian
2021	J	`jnl`	Sketched quantile additive functional regression. Neurocomputing Yingying Zhang, Heng Lian
2020	J	`jnl`	A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model. Comput. Stat. Data Anal. Shaogao Lv, Zengyan Fan, Heng Lian, Taiji Suzuki, Kenji Fukumizu
2020	J	`jnl`	Debiasing and Distributed Estimation for High-Dimensional Quantile Regression. IEEE Trans. Neural Networks Learn. Syst. Weihua Zhao, Fode Zhang, Heng Lian
2020	J	`jnl`	Nonlinear functional canonical correlation analysis via distance covariance. J. Multivar. Anal. Hanbing Zhu, Rui Li, Riquan Zhang, Heng Lian
2020	J	`jnl`	Partially functional linear regression in reproducing kernel Hilbert spaces. Comput. Stat. Data Anal. Xia Cui, Hongmei Lin, Heng Lian
2020	J	`jnl`	Randomized sketches for kernel CCA. Neural Networks Heng Lian, Fode Zhang, Wenqi Lu
2020	J	`jnl`	Randomized sketches for sparse additive models. Neurocomputing Fode Zhang, Xuejun Wang, Rui Li, Heng Lian
2019	J	`jnl`	Estimation and testing for partially functional linear errors-in-variables models. J. Multivar. Anal. Hanbing Zhu, Riquan Zhang, Zhou Yu, Heng Lian, Yanghui Liu
2019	J	`jnl`	Estimation for single-index models via martingale difference divergence. Comput. Stat. Data Anal. Jicai Liu, Peirong Xu, Heng Lian
2019	J	`jnl`	Pursuit of dynamic structure in quantile additive models with longitudinal data. Comput. Stat. Data Anal. Xia Cui, Weihua Zhao, Heng Lian, Hua Liang
2019	J	`jnl`	Rank reduction for high-dimensional generalized additive models. J. Multivar. Anal. Hongmei Lin, Heng Lian, Hua Liang
2019	J	`jnl`	Reduced rank modeling for functional regression with functional responses. J. Multivar. Anal. Hongmei Lin, Xuejun Jiang, Heng Lian, Weiping Zhang
2019	J	`jnl`	Regression adjustment for treatment effect with multicollinearity in high dimensions. Comput. Stat. Data Anal. Lili Yue, Gaorong Li, Heng Lian, Xiang Wan
2018	J	`jnl`	A principal varying-coefficient model for quantile regression: Joint variable selection and dimension reduction. Comput. Stat. Data Anal. Weihua Zhao, Xuejun Jiang, Heng Lian
2018	J	`jnl`	Estimation and testing for time-varying quantile single-index models with longitudinal data. Comput. Stat. Data Anal. Jianbo Li, Heng Lian, Xuejun Jiang, Xinyuan Song
2018	J	`jnl`	On the sign consistency of the Lasso for the high-dimensional Cox model. J. Multivar. Anal. Shaogao Lv, Mengying You, Huazhen Lin, Heng Lian, Jian Huang
2018	J	`jnl`	Quantile regression for additive coefficient models in high dimensions. J. Multivar. Anal. Zengyan Fan, Heng Lian
2018	J	`jnl`	Time-varying quantile single-index model for multivariate responses. Comput. Stat. Data Anal. Weihua Zhao, Yan Zhou, Heng Lian
2017	J	`jnl`	Composite quantile regression for correlated data. Comput. Stat. Data Anal. Weihua Zhao, Heng Lian, Xinyuan Song
2017	J	`jnl`	Divide-and-Conquer for Debiased $l_1$-norm Support Vector Machine in Ultra-high Dimensions. J. Mach. Learn. Res. Heng Lian, Zengyan Fan
2017	J	`jnl`	Estimation and model identification of longitudinal data time-varying nonparametric models. J. Multivar. Anal. Shu Liu, Jinhong You, Heng Lian
2017	J	`jnl`	Estimation and variable selection for quantile partially linear single-index models. J. Multivar. Anal. Yuankun Zhang, Heng Lian, Yan Yu
2017	J	`jnl`	Profile forward regression screening for ultra-high dimensional semiparametric varying coefficient partially linear models. J. Multivar. Anal. Yujie Li, Gaorong Li, Heng Lian, Tiejun Tong
2017	J	`jnl`	Quantile index coefficient model with variable selection. J. Multivar. Anal. Weihua Zhao, Heng Lian
2016	J	`jnl`	A new nested Cholesky decomposition and estimation for the covariance matrix of bivariate longitudinal data. Comput. Stat. Data Anal. Sanying Feng, Heng Lian, Liugen Xue
2016	J	`jnl`	Estimation and variable selection for proportional response data with partially linear single-index models. Comput. Stat. Data Anal. Weihua Zhao, Heng Lian, Riquan Zhang, Peng Lai
2016	J	`jnl`	Mean and quantile boosting for partially linear additive models. Stat. Comput. Xingyu Tang, Heng Lian
2016	J	`jnl`	Minimax convergence rates for kernel CCA. J. Multivar. Anal. Zengyan Fan, Heng Lian
2016	J	`jnl`	Nonconvex penalized reduced rank regression and its oracle properties in high dimensions. J. Multivar. Anal. Heng Lian, Yongdai Kim
2016	J	`jnl`	Posterior convergence for Bayesian functional linear regression. J. Multivar. Anal. Heng Lian, Taeryon Choi, Jie Meng, Seongil Jo
2016	J	`jnl`	Reduced rank regression with possibly non-smooth criterion functions: An empirical likelihood approach. Comput. Stat. Data Anal. Sanying Feng, Heng Lian, Fukang Zhu
2016	J	`jnl`	Robust closed-form estimators for the integer-valued GARCH (1, 1) model. Comput. Stat. Data Anal. Qi Li, Heng Lian, Fukang Zhu
2016	J	`jnl`	Separation of linear and index covariates in partially linear single-index models. J. Multivar. Anal. Heng Lian, Hua Liang
2016	J	`jnl`	The Expectation-Maximization approach for Bayesian quantile regression. Comput. Stat. Data Anal. Kaifeng Zhao, Heng Lian
2015	J	`jnl`	A Note on Application of Nesterov's Method in Solving Lasso-Type Problems. Commun. Stat. Simul. Comput. Ye Tian, Heng Lian
2015	J	`jnl`	Bayesian quantile regression for partially linear additive models. Stat. Comput. Yuao Hu, Kaifeng Zhao, Heng Lian
2015	J	`jnl`	Minimax prediction for functional linear regression with functional responses in reproducing kernel Hilbert spaces. J. Multivar. Anal. Heng Lian
2015	J	`jnl`	Parametric and semiparametric reduced-rank regression with flexible sparsity. J. Multivar. Anal. Heng Lian, Sanying Feng, Kaifeng Zhao
2015	J	`jnl`	Quantile regression for dynamic partially linear varying coefficient time series models. J. Multivar. Anal. Heng Lian
2015	J	`jnl`	Simultaneous estimation of linear conditional quantiles with penalized splines. J. Multivar. Anal. Heng Lian, Jie Meng, Zengyan Fan
2015	J	`jnl`	Spline estimator for simultaneous variable selection and constant coefficient identification in high-dimensional generalized varying-coefficient models. J. Multivar. Anal. Heng Lian, Jie Meng, Kaifeng Zhao
2015	J	`jnl`	Variable selection and estimation for partially linear single-index models with longitudinal data. Stat. Comput. Gaorong Li, Peng Lai, Heng Lian
2014	J	`jnl`	Empirical likelihood inference for general transformation models with right censored data. Stat. Comput. Jianbo Li, Zhensheng Huang, Heng Lian
2014	J	`jnl`	Partially linear structure identification in generalized additive models with NP-dimensionality. Comput. Stat. Data Anal. Heng Lian, Pang Du, Yuanzhang Li, Hua Liang
2014	J	`jnl`	SCAD-penalized regression in additive partially linear proportional hazards models with an ultra-high-dimensional linear part. J. Multivar. Anal. Heng Lian, Jianbo Li, Xingyu Tang
2014	J	`jnl`	Semiparametric Bayesian information criterion for model selection in ultra-high dimensional additive models. J. Multivar. Anal. Heng Lian
2014	J	`jnl`	Series expansion for functional sufficient dimension reduction. J. Multivar. Anal. Heng Lian, Gaorong Li
2014	J	`jnl`	Variational inferences for partially linear additive models with variable selection. Comput. Stat. Data Anal. Kaifeng Zhao, Heng Lian
2013	J	`jnl`	A simple and efficient algorithm for fused lasso signal approximator with convex loss function. Comput. Stat. Lichun Wang, Yuan You, Heng Lian
2013	J	`jnl`	Automatic variable selection for longitudinal generalized linear models. Comput. Stat. Data Anal. Gaorong Li, Heng Lian, Sanying Feng, Lixing Zhu
2013	J	`jnl`	Bayesian quantile regression for single-index models. Stat. Comput. Yuao Hu, Robert B. Gramacy, Heng Lian
2013	J	`jnl`	Empirical likelihood for partially linear proportional hazards models with growing dimensions. J. Multivar. Anal. Xingyu Tang, Jianbo Li, Heng Lian
2013	J	`jnl`	Quadratic inference functions for partially linear single-index models with longitudinal data. J. Multivar. Anal. Peng Lai, Gaorong Li, Heng Lian
2013	J	`jnl`	Shrinkage variable selection and estimation in proportional hazards models with additive structure and high dimensionality. Comput. Stat. Data Anal. Heng Lian, Jianbo Li, Yuao Hu
2013	J	`jnl`	Sparse-smooth regularized singular value decomposition. J. Multivar. Anal. Zhaoping Hong, Heng Lian
2012	J	`jnl`	BOPA: A Bayesian hierarchical model for outlier expression detection. Comput. Stat. Data Anal. Zhaoping Hong, Heng Lian
2012	J	`jnl`	Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data. J. Multivar. Anal. Peng Lai, Qihua Wang, Heng Lian
2012	J	`jnl`	Gaussian Process Single-Index Models as Emulators for Computer Experiments. Technometrics Robert B. Gramacy, Heng Lian
2012	J	`jnl`	On feature selection with principal component analysis for one-class SVM. Pattern Recognit. Lett. Heng Lian
2012	J	`jnl`	Time-varying coefficient estimation in differential equation models with noisy time-varying covariates. J. Multivar. Anal. Zhaoping Hong, Heng Lian
2011	J	`jnl`	Semi-varying coefficient models with a diverging number of components. J. Multivar. Anal. Gaorong Li, Liugen Xue, Heng Lian
2010	J	`jnl`	Sparse Bayesian hierarchical modeling of high-dimensional clustering problems. J. Multivar. Anal. Heng Lian
2010	J	`jnl`	Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images. Pattern Recognit. Aditya Chopra, Heng Lian
2009	J	`jnl`	Bayesian Nonlinear Principal Component Analysis Using Random Fields. IEEE Trans. Pattern Anal. Mach. Intell. Heng Lian
2009	J	`jnl`	Total Variation, Adaptive Total Variation and Nonconvex Smoothly Clipped Absolute Deviation Penalty for Denoising Blocky Images CoRR Aditya Chopra, Heng Lian
2008	J	`jnl`	Automated mapping of large-scale chromatin structure in ENCODE. Bioinform. Heng Lian, William A. Thompson, Robert E. Thurman, John A. Stamatoyannopoulos, William Stafford Noble, Charles E. Lawrence
2008	J	`jnl`	Bayesian Nonlinear Principal Component Analysis Using Random Fields CoRR Heng Lian
2007	J	`jnl`	On the Consistency of Bayesian Function Approximation Using Step Functions. Neural Comput. Heng Lian
2007	J	`jnl`	Variational local structure estimation for image super-resolution CoRR Heng Lian
2006	B	`conf`	Variational Local Structure Estimation for Image Super-Resolution. ICIP Heng Lian